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Updated: Aug 15, 2025

Characterization of the Sense of Agency over the Actions of Neural-machine Interface-operated Prostheses
Published on: January 7, 2019
AI in the hands of imperfect users
Kristin M Kostick-Quenet1, Sara Gerke2
1Center for Medical Ethics and Health Policy, Baylor College of Medicine, Houston, TX, USA. Kristin.kostick@bcm.edu.
Abstract:
As the use of artificial intelligence and machine learning (AI/ML) continues to expand in healthcare, much attention has been given to mitigating bias in algorithms to ensure they are employed fairly and transparently. Less attention has fallen to addressing potential bias among AI/ML's human users or factors that influence user reliance. We argue for a systematic approach to identifying the existence and impacts of user biases while using AI/ML tools and call for the development of embedded interface design features, drawing on insights from decision science and behavioral economics, to nudge users towards more critical and reflective decision making using AI/ML.
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